Zinc supplementation to improve prognosis in patients with compensated advanced chronic liver disease: a multicenter, randomized, double-blind, placebo-controlled clinical trial
Bibliographic record
Abstract
Zinc homeostasis could play a role in compensated advanced chronic liver disease, and its supplementation has been linked to improvement in liver function, a decrease of hepatic complications, and reduction in HCC incidence. Compensated advanced chronic liver disease encompasses a heterogeneous group of patients with variable risks of clinically significant portal hypertension and clinical events. The ANTICIPATE model is a validated model for stratifying these risks. Our aim is to demonstrate that zinc administration can reduce the rate and risk of presenting clinical events (first decompensation, HCC, death, and liver transplantation). This study protocol describes an ongoing phase III, national, multicenter, randomized, double-blind clinical trial that will enroll 300 patients to receive either the trial treatment (zinc acexamate) or placebo. An inclusion period of 42 months is planned, with a minimum follow-up of 2 years. Our principal hypothesis is that zinc could modify the natural history of patients with compensated advanced chronic liver disease, with an overall improvement in prognosis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".